Jane M. Olson

Overview of QTL mapping software and introduction to map manager QT.

Abstract. At least ten software packages are available for marker-based detection and localization of loci contributing to quantitative traits in experimental animals and plants. Many of these have unique strengths or situations in which they are particularly useful. Six were developed by or in collaboration with plant geneticists and may not be well known to mammalian geneticists. These software packages are reviewed here and compared with a previously undescribed program, Map Manager QT, a Mac OS microcomputer program for mapping quantitative trait loci in populations derived from backcrosses, intercrosses, and recombinant inbred lines. Map Manager QT is an enhanced version of Map Manager Classic (Map Manager v2.6.5, Manly 1993), designed for mapping Mendelian loci. This review describes the methods Map Manager QT uses for mapping quantitative trait loci and describes other features that differ from those in Map Manager Classic. A complete description of both Map Manager Classic and Map Manager QT is available in the user manual, the on-line version of which can be found at http://mcbio.med.buffalo.edu/MMM/MMM.html.

Segregation at three loci explains familial and population risk in Hirschsprung disease

Hirschsprung disease (HSCR), the most common hereditary cause of intestinal obstruction, shows considerable variation and complex inheritance. Coding sequence mutations in RET, GDNF, EDNRB, EDN3 and SOX10 lead to long-segment (L-HSCR) and syndromic HSCR but fail to explain the transmission of the much more common short-segment form (S-HSCR). We conducted a genome scan in families with S-HSCR and identified susceptibility loci at 3p21, 10q11 and 19q12 that seem to be necessary and sufficient to explain recurrence risk and population incidence. The gene at 10q11 is probably RET, supporting its crucial role in all forms of HSCR; however, coding sequence mutations are present in only 40% of linked families, suggesting the importance of noncoding variation. Here we show oligogenic inheritance of S-HSCR, the 3p21 and 19q12 loci as RET-dependent modifiers, and a parent-of-origin effect at RET. This study demonstrates by a complete genetic dissection why the inheritance pattern of S-HSCR is nonmendelian.

Model-Free Linkage Analysis with Covariates Confirms Linkage of Prostate Cancer to Chromosomes 1 and 4

As with many complex genetic diseases, genome scans for prostate cancer have given conflicting results, often failing to provide replication of previous findings. One factor contributing to the lack of consistency across studies is locus heterogeneity, which can weaken or even eliminate evidence for linkage that is present only in a subset of families. Currently, most analyses either fail to account for locus heterogeneity or attempt to account for it only by partitioning data sets into smaller and smaller portions. In the present study, we model locus heterogeneity among affected sib pairs with prostate cancer by including covariates in the linkage analysis that serve as surrogate measures of between-family linkage differences. The model is a modification of the Olson conditional logistic model for affected relative pairs. By including Gleason score, age at onset, male-to-male transmission, and/or number of affected first-degree family members as covariates, we detected linkage near three locations that were previously identified by linkage (1q24-25 [HPC1; LOD score 3.25, P=.00012], 1q42.2-43 [PCAP; LOD score 2.84, P=.0030], and 4q [LOD score 2.80, P=.00038]), near the androgen-receptor locus on Xq12-13 (AR; LOD score 3.06, P=.00053), and at five new locations (LOD score > 2.5). Without covariates, only a few weak-to-moderate linkage signals were found, none of which replicate findings of previous genome scans. We conclude that covariate-based linkage analysis greatly improves the likelihood that linked regions will be found by incorporation of information about heterogeneity within the sample.

Genome Scan of Human Systemic Lupus Erythematosus by Regression Modeling: Evidence of Linkage and Epistasis at 4p16-15.2

Systemic lupus erythematosus (SLE) is a complex autoimmune disorder involving at least hormonal, environmental, and genetic factors. Familial aggregation, a 2%-3% sibling recurrence rate, monozygotic twin concordance >20%, association with several candidate genes, as well as the results of five genome scans support a genetic component. We present here the results of a genome scan of 126 pedigrees multiplex for SLE, including 469 sibling pairs (affected and unaffected) and 175 affected relative pairs. Using the revised multipoint Haseman-Elston regression technique for concordant and discordant sibling pairs and a conditional logistic regression technique for affected relative pairs, we identify a novel linkage to chromosome 4p16-15.2 (P=.0003 and LOD=3.84) and present evidence of an epistatic interaction between chromosome 4p16-15.2 and chromosome 5p15 in our European American families. We confirm the evidence of linkage to chromosome 4p16-15.2 in European American families using data from an independent pedigree collection. In addition, our data support the published results of three independent studies for nine purportedly linked regions and agree with the previously published results from a subset of these data for three regions. In summary, results from two new analytical techniques establish and confirm linkage with SLE at 4p16-15.2, indicate epistasis between 4p16-15.2 and 5p15, and confirm other linkage effects with SLE that have been reported elsewhere.

A General Conditional-Logistic Model for Affected-Relative-Pair Linkage Studies

Model-free LOD-score methods are often employed to detect linkage between marker loci and common diseases, with samples of affected sib pairs. Although extensions of the basic one-disease-locus model have been proposed that allow separate inclusion of other types of affected relative pairs, discordant relative pairs, covariates, or additional disease loci, a unified framework that can handle all of these features has been lacking. In this report, I propose a conditional-logistic parameterization that generalizes easily to include all of these features. Two data examples, one using simulated data and one using type 1 diabetes, illustrate applications of the models.

Genome Scan for Familial Abdominal Aortic Aneurysm Using Sex and Family History as Covariates Suggests Genetic Heterogeneity and Identifies Linkage to Chromosome 19q13

Background—Abdominal aortic aneurysm (AAA) is a relatively common disease, with 1% to 2% of the population harboring aneurysms. Genetic risk factors are likely to contribute to the development of AAAs, although no such risk factors have been identified. Methods and Results—We performed a whole-genome scan of AAA using affected-relative-pair (ARP) linkage analysis that includes covariates to allow for genetic heterogeneity. We found strong evidence of linkage (logarithm of odds [LOD] score=4.64) to a region near marker D19S433 at 51.88 centimorgans (cM) on chromosome 19 with 36 families (75 ARPs) when including sex and the number of affected first-degree relatives of the proband (Naff) as covariates. We then genotyped 83 additional families for the same markers and typed additional markers for all families and obtained a LOD score of 4.75 (P =0.00014) with sex, Naff, and their interaction as covariates near marker D19S416 (58.69 cM). We also identified a region on chromosome 4 with a LOD score of 3.73 (P =0.0012) near marker D4S1644 using the same covariate model as for chromosome 19. Conclusions—Our results provide evidence for genetic heterogeneity and the presence of susceptibility loci for AAA on chromosomes 19q13 and 4q31.

A Second Locus for Very-Late-Onset Alzheimer Disease: A Genome Scan Reveals Linkage to 20p and Epistasis between 20p and the Amyloid Precursor Protein Region

We used a covariate-based linkage method to reanalyze genome scan data from affected sibships collected by the Alzheimer Disease (AD) Genetics Initiative of the National Institute of Mental Health. As reported in an earlier article, the amyloid-beta precursor protein (APP) region is strongly linked to affected sib pairs of the oldest current age (i.e., age either at last exam or at death) who lack E4 alleles at the apolipoprotein E (ApoE) locus. We now report that a region on 20p shows the same pattern. A model that includes current age and the number of E2 alleles as covariates gives a LOD score of 4.1. The signal on 20p is near the location of the gene coding for cystatin-C, previously shown to be associated with late-onset AD and to codeposit with APP in the brains of patients with AD. Two-locus analysis provides evidence of strong epistasis between 20p and the APP region, limited to the oldest age group and to those lacking ApoE4 alleles. We speculate that high-risk polymorphisms in both regions produce a biological interaction between these two proteins that increases susceptibility to a very-late-onset form of AD.

Search for intracranial aneurysm susceptibility gene(s) using Finnish families

BackgroundCerebrovascular disease is the third leading cause of death in the United States, and about one-fourth of cerebrovascular deaths are attributed to ruptured intracranial aneurysms (IA). Epidemiological evidence suggests that IAs cluster in families, and are therefore probably genetic. Identification of individuals at risk for developing IAs by genetic tests will allow concentration of diagnostic imaging on high-risk individuals. We used model-free linkage analysis based on allele sharing with a two-stage design for a genome-wide scan to identify chromosomal regions that may harbor IA loci.MethodsWe previously estimated sibling relative risk in the Finnish population at between 9 and 16, and proceeded with a genome-wide scan for loci predisposing to IA. In 85 Finnish families with two or more affected members, 48 affected sibling pairs (ASPs) were available for our genetic study. Power calculations indicated that 48 ASPs were adequate to identify chromosomal regions likely to harbor predisposing genes and that a liberal stage I lod score threshold of 0.8 provided a reasonable balance between detection of false positive regions and failure to detect real loci with moderate effect.ResultsSeven chromosomal regions exceeded the stage I lod score threshold of 0.8 and five exceeded 1.0. The most significant region, on chromosome 19q, had a maximum multipoint lod score (MLS) of 2.6.ConclusionsOur study provides evidence for the locations of genes predisposing to IA. Further studies are necessary to elucidate the genes and their role in the pathophysiology of IA, and to design genetic tests.

Intracranial Aneurysms in Finnish Families: Confirmation of Linkage and Refinement of the Interval to Chromosome 19q13.3

We recently reported a two-stage genomewide screen of 48 sib pairs affected with intracranial aneurysms (IAs) that revealed suggestive linkage to chromosome 19q13, with a LOD score of 2.58. The region supporting linkage spanned approximately 22 cM. Here, we report a follow-up study of the locus at 19q13, with a sample size expanded to 139 affected sib pairs, along with 83 other affected relative pairs (222 affected relative pairs in total). Suggestive linkage was observed in both independent sample sets, and linkage was significant in the combined set at 70 cM (LOD score 3.50; P=.00006) and at 80 cM (LOD score 3.93; P=.00002). Linkage was highly significant at 70 cM (LOD score 5.70; P=.000001) and at 80 cM (LOD score 3.99; P=.00005) when a covariate measuring the number of affected individuals in the nuclear family was included. To evaluate further the contribution to the linkage signal from families with more than two affected relatives, we performed model-based linkage analysis with a recessive model and a range of penetrances, and we obtained maximum linkage at 70 cM (LOD score 3.16; P=.00007) with a penetrance of 0.3. We then estimated location by using GENEFINDER. The most likely location for a gene predisposing to IAs in the Finnish population is in a region with a 95% confidence interval of 11.6 cM (P=.00007) centered 2.0 cM proximal to D19S246.

Candidate-Gene Association Study of Mothers with Pre-Eclampsia, and Their Infants, Analyzing 775 SNPs in 190 Genes

Pre-eclampsia (PE) affects 5–7% of pregnancies in the US, and is a leading cause of maternal death and perinatal morbidity and mortality worldwide. To identify genes with a role in PE, we conducted a large-scale association study evaluating 775 SNPs in 190 candidate genes selected for a potential role in obstetrical complications. SNP discovery was performed by DNA sequencing, and genotyping was carried out in a high-throughput facility using the MassARRAYTM System. Women with PE (n = 394) and their offspring (n = 324) were compared with control women (n = 602) and their offspring (n = 631) from the same hospital-based population. Haplotypes were estimated for each gene using the EM algorithm, and empirical p values were obtained for a logistic regression-based score test, adjusted for significant covariates. An interaction model between maternal and offspring genotypes was also evaluated. The most significant findings for association with PE were COL1A1 (p = 0.0011) and IL1A (p = 0.0014) for the maternal genotype, and PLAUR (p = 0.0008) for the offspring genotype. Common candidate genes for PE, including MTHFR and NOS3, were not significantly associated with PE. For the interaction model, SNPs within IGF1 (p = 0.0035) and IL4R (p = 0.0036) gave the most significant results. This study is one of the most comprehensive genetic association studies of PE to date, including an evaluation of offspring genotypes that have rarely been considered in previous studies. Although we did not identify statistically significant evidence of association for any of the candidate loci evaluated here after adjusting for multiple testing using the false discovery rate, additional compelling evidence exists, including multiple SNPs with nominally significant p values in COL1A1 and the IL1A region, and previous reports of association for IL1A, to support continued interest in these genes as candidates for PE. Identification of the genetic regulators of PE may have broader implications, since women with PE are at increased risk of death from cardiovascular diseases later in life.